General Information

Prospective Students

Intent to Enroll

After we have notified you of your acceptance into the degree program,
you need to communicate your intent to enroll in the program or to deny
admission to the program by April 15. You can do this through a
link sent in your admissions email.

Registration and Enrollment

The University will send you numerous emails about how to pay your tuition
and fees, as well as how to enroll in courses. Look for these emails and if
you do not receive emails during the months of June and July about these matters,
please contact Breanne Tcheng.

Orientation

Orientation and a Pre-Semester Leadership Intensive course will take place on campus from August 11-22, 2014 and attendance
is mandatory. This is an important time for the cohort to build community,
receive important information, and practice vital skills for the leadership
component of the program. The schedule is posted in bSpace and was also
sent via email. Again, if you do not receive emails regarding this matter,
please contact Breanne Tcheng.

Timeline

The campuswide Academic Calendar has all campus deadlines, holidays, and instructional dates. The list below includes specific dates for EECS MEng students.

Program Requirements by Area

Data Science and Systems

All EECS MEng students should expect to complete four (4) technical courses within the
EECS department at the graduate level, the Fung Institute's engineering leadership curriculum,
as well as a capstone project that will be hosted by the EECS department.

2014-2015 Capstone Projects

For the capstone projects for Master of Engineering in Electrical
Engineering and Computer Science (EECS) our department believes that
the students are going to have a significantly better experience if
the projects are followed closely by an EECS professor throughout the
academic year. To ensure this, we have asked the faculty in each area
for which the Master of Engineering is offered in our department to
formulate one or more project ideas that the incoming students will
have to choose from. We list below the titles and faculty advisor for
these capstone choices in the area. Depending on the number of
enrolled students in the area, we may run only a subset of these
project ideas.

Project 1 Title - Anomaly Detection for Internet Video Analytics (advisor Prof. George Necula in collaboration with Conviva Inc.)
Description - Conviva Inc. is the leading provider of Online Video
Quality Analytics, managing tens of billions of online video streams each year.
This vast amount of data contains not-yet-tapped information about viewer and
device trends, content penetration, and network performance. Students will work
as a team to build a scalable analysis and machine-learning framework that can
process real-time video analytics data. On top of this platform students will
develop individually or in smaller teams a number of data mining analyses. The
choice of analyses is vast, and we will pick based on student interest and
capabilities of the platform that we will develop. Examples are: social
analytics correlation (analyze social media, e.g., positive or negative comments
about shows, and find correlations with measured quality), viral video detector
(detect when a video goes viral), device/CDN/ISP performance (compare quality of
delivery for various networks and devices), bitrate and encoding profile
recommendation (based on measured quality for the device and the network
recommend best set of bitrates and video encoding parameters), subscriber
loyalty (understand subscriber retention over various user groups and how it
correlates with quality), subscriber content loyalty (which content groups --
genres, artists -- bring in most loyal viewers), impact of mobile devices on
engagement/retention.

Project 2 Title - Large-Scale Text Analysis Techniques for the Visual Analysis
of Scientific Articles (advisor Prof. Laurent El Ghaoui)
Description - This project involves the implementation of large-scale text analysis
techniques for the visual analysis of scientific articles in streaming fashion. Ultimately
the goal will be to allow a user to type the name of a topic (say, "natural language
processing"), and in response the server shows a timeline of the sub-topics involved,
as well as suggests a short reading list. The StatNews project (at statnews.org) is
already in place to analyze news articles. This particular project will focus on
document similarity and natural language processing techniques for scientific papers
and implement the approach in the statnews server. Skills involved include Python,
MySQL, and of course interest in machine learning and algorithms for large-scale
applications. The project team will interact with El Ghaoui's research group.

Project 3 Title - Analytics Middleware for the Internet of Everything (advisor Prof. Michael Franklin in collaboration with Cisco Systems)
Description - The Internet of Everything will see a world with an explosion of connected devices providing large volumes of data in aggregate across wide area networks. Analytics over such widely distributed data is not feasible with modern Big Data systems that focus on distributing computation within a single data center. There are, however, many significant use cases where it would be very valuable to organize and process the data very close to where it was generated across a wide area network, one primary domain where these conditions are true is "internet of things". More specifically, relevant uses for this approach include situations where: (a) the data being produced is very large and cannot be moved to a central site within a reasonable time or cost, (b) the newly produced data needs to be acted upon in real-time where it is generated either because of latency or autonomy considerations, and (c) the network conditions change dynamically and dramatically affect how and what computations must be distributed. In summary, modern network-aware applications that operate over geographically distributed data will need a sophisticated programming model. Solutions to be investigated include both topology and cost aware approaches to distributed analytics, and performance acceleration techniques such as compression, sampling and data summarization through coresets and/or other techniques. Students working on this project will design and prototype such a data-centric middleware infrastructure that allows application programmers to easily consume distributed data from the network and also control the sources of the data as necessary.

Technical Courses

At least two of your four technical courses should be chosen from the list below. The remaining
technical courses should be chosen from your own or another MEng area of concentration within the EECS Department.

Physical Electronics and Integrated Circuits

All EECS MEng students should expect to complete four (4) technical courses within the
EECS department at the graduate level, the Fung Institute's engineering leadership curriculum,
as well as a capstone project that will be hosted by the EECS department.

The Physical Electronics and Integrated Circuits areas have been combined due to the
many commonalities between them. Students in either area may choose from a combined set
of capstone projects and technical courses as shown below.

2014-2015 Capstone Projects

For the capstone projects for Master of Engineering in Electrical
Engineering and Computer Science (EECS) our department believes that
the students are going to have a significantly better experience if
the projects are followed closely by an EECS professor throughout the
academic year. To ensure this, we have asked the faculty in each area
for which the Master of Engineering is offered in our department to
formulate one or more project ideas that the incoming students will
have to choose from. We list below the titles and faculty advisor for
these capstone choices in the area. Depending on the number of
enrolled students in the area, we may run only a subset of these
project ideas.

Project 1 Title - Integrative Smart Solar Optofluidics for Energy and Healthcare (advisor Prof. Luke P. Lee)
BSAC, Departments of Bioengineering and EECS
Description - In this project, we are developing digital healthcare systems for precision medicine, which will be foundation for preventive personalized healthcare by creating smartphone-based Integrated Molecular Diagnostic Systems (iMDx). This smartphone-based iMDx is automated, sensitive, specific, user-friendly, robust, rapid, easy-to-use, and portable, can revolutionize future medicine. We design low-powered and precise sample preparation and new detection methods by sample amplification and ultrafast signal transduction.
This digital healthcare system holds the potential to breakthrough the number of problems brought into the field of healthcare and life sciences today.

Project 2 Title - An Analysis of On-Chip Vacuum Electronics for Grid-Scale Integrated Circuits (advisor Prof. Vivek Subramanian)
Description - In this project, students will evaluate the viability of on-chip vacuum electronics for kilovolt level switching, with the goal of realizing a technology for realizing an integrated circuit technology for smart grids. Students will review literature on planar vacuum tubes to develop models for high-voltage operation, will simulate vacuum tube structures to design candidate vacuum tubes, and will define process flows for fabrication of such devices on silicon; these will ultimately be fabricated in the Marvell Nanolab, and characterized to validate designs.

Project 3 Title - Petabit switch-fabric design (advisors Profs. Elad Alon and Vladimir Stojanovic)
Description - In this project the team will explore the circuits and architectures for
building a 1000-port switch-fabric with petabit bisection bandwidth, for emerging cloud-computing
applications. The fabric will consist of high-speed electrical or photonic SerDes I/O and a
variety of crossbar architectures. The project will build-up the high-speed analog/mixed-signal
and digital design skills as well as exposure to silicon-photonics and switch architectures.

Project 4 Title - Next generation memory interfaces (advisors Profs. Elad Alon and Vladimir Stojanovic)
Description - In this project the team will build a next generation memory controller
and high-speed link interface, for 3D stacked memory chips. The project will build-up the
high-speed analog/mixed-signal and digital design skills as well as exposure to internal
modern DRAM organization and design trade-offs.

Project 5 Title - Productizing ABCD (Accurate Booleanization of Continuous Dynamics) (advisor Prof. Jaijeet Roychowdhury)
Description - ABCD, an ongoing research project, comprises theory, algorithms
and software for approximating continuous ("analog") systems using
purely Boolean representations, so that they can be verified
seamlessly along with other digital systems. In this project, you
will explore:

finding good AMS (analog/mixed-signal) circuit use cases and using ABCD
to Booleanize and verify them within a system.

figuring out what works well in ABCD, what does not, and what
additional capabilities are required.

a market study to figure out what the industry would really
want in such a tool, and making a business case for ABCD.

optionally: contribute to the code and research.

Project 6 Title - Transistor Circuits for a MEMS-Based Wireless Transceiver (advisor Prof. Clark Nguyen)
Description - This project entails the design and layout of circuit blocks needed
to implement a wireless transceiver that combines transistors and MEMS devices to achieve
sub-50uW power consumption. The needed blocks include a sustaining circuit for a MEMS-based
oscillator, an energy sensing amplifier, demodulation blocks, and a Class E power amplifier.

Project 7 Title - Computational CellScope and Computation Illumination for Upgrading an Optical Microscope (advisor Prof. Laura Waller) - this project is cross-listed with
the Signal Processing & Communications area.
Description - We are building an inexpensive optical microscope based on mobile
phone technology (CellScope). By implementing illumination patterning in Fourier space, we
can create a computational imaging system that can image 3D and phase information. The
new computational CellScope will be used for diagnosing tropical diseases in underdeveloped
countries.

We are developing new methods for optical microscopy that use
sophisticated image processing and Fourier optics to achieve multiple contrast modes
in a commercial microscope with minimal hardware modification. We will provide
super-resolution capabilities with phase imaging, so that the microscope can
achieve gigapixel images with diffraction-limited resolution.

Project 8 Title - Post-CMOS circuit and logic design with spintronic/nanomagnetic devices (advisors Profs. Elad Alon and Vladimir Stojanovic)
Description - In this project the team will evaluate different circuit and logic
design styles with post-CMOS Spin Transfer Torque (STT) devices, in particular Spin-Valve/Magnetic
Tunneling Junction (SV/MTJ) devices. These devices operate at extremely low supply voltages
(10s of mV) but have on-to-off current ratios much smaller than in CMOS (typically 3-5).
The team will develop a variety of circuit techniques that leverage low-voltage operation
of SV/MTJ devices while mitigating the leakage effects. The techniques will be applied to
processor datapath logic as well as high-speed link SerDes. The project will build-up the
high-speed circuit, low-power digital and mixed-signal design skills, as well as exposure
to operation of several post-CMOS device technologies.

Robotics and Embedded Software

Program Requirements

All EECS MEng students should expect to complete four (4) technical courses within the
EECS department at the graduate level, the Fung Institute's engineering leadership curriculum,
as well as a capstone project that will be hosted by the EECS department.

2014-2015 Capstone Projects

For the capstone projects for Master of Engineering in Electrical
Engineering and Computer Science (EECS) our department believes that
the students are going to have a significantly better experience if
the projects are followed closely by an EECS professor throughout the
academic year. To ensure this, we have asked the faculty in each area
for which the Master of Engineering is offered in our department to
formulate one or more project ideas that the incoming students will
have to choose from. We list below the titles and faculty advisor for
these capstone choices in the area. Depending on the number of
enrolled students in the area, we may run only a subset of these
project ideas.

Project 1 Title - Model-Based Embedded Software (advisors
Profs. Edward Lee and Sanjit Seshia)
Description - Recently, a plethora of small, open-source embedded computing platforms such
as Rasberry PI and Arduino have emerged, competing with more proprietary designs.
A rich ecosystem of applications and add-on hardware have emerged that enable
hobbyists and serious designers to quickly prototype designs, and even to design
and deploy commercial products. The software development environments for such
processors are fairly conventional IDEs and C programming environments, with
libraries provided for peripheral devices. The purpose of this project to design
and construct a model-based design environment for software for such devices.
Instead of constructing C programs, application designers will build graphical
models representing state machines, dataflow diagrams, and discrete-event systems,
that describe the application, and a code generator will produce the embedded C code.
The goals of the project are:

To understand the market for such low-level devices and identify the most lively
ecosystems and best opportunities for having an impact on the market.

To assess the risk factors in a code generation approach, including inefficient code, excessive energy consumption, steep learning curves, and extensibility and and adaptability.

To assess opportunities provided by model-based design, such as more reliable programs, opportunities for formal verification, opportunities for optimization
of energy consumption, testability, determinism, and ease of design and/or adaptation.

To design and build prototypes for experiments that can measure key risk factors
and opportunities.

To devise one or more compelling demonstrations that illustrate one or more of
of the opportunities that can be realized with the approach.

Good software skills and experience with embedded systems are a definite plus for this project.

Project 2 Title - Expanded system design and implementation of Cell phone/client/server application for tele-monitoring heart patients (advisor Prof. Ruzena Bajcsy)
Description - The current system works as follows: elderly heart patients who are released from hospital are given cell phone with provider plan and are asked to carry the phone while they are moving around (measuring their physical activity). Every evening they are prompted to answer questions related to their subjective health as well as to how much information they are willing to share with respect to privacy.
All this information(the measurements as well as textual answers) is transmitted and stored at UC Berkeley server.
In the expanded system we want to a) improve the user interface on the cell phone application and b) we need to redesign the client /server so that it can accommodate new sensors (blood pressure, heart beat, breathing rhythm,and their like) and on the server site create flexible data structure for these new sensory modalities.

Project 3 Title - Data Analytics for Societal Scale Cyber Physical Systems (advisor Prof. Shankar Sastry)
Description - Societal Scale Cyber Physical Systems (CPS) refers to the cyber instrumentation of the physical back bone of many of our societal systems, such as the smart grid, building systems, transportation, water, gas, etc.
With the availability of inexpensive wireless sensor networks as the cyber backbone of such societal CPS systems, there is a need for analyzing large amounts of data in real time for reliability, resilience to (cyber) attack, revenue protection and privacy. For example, it is emerging that the underpinnings of the smart grid lies in data disaggregation algorithms and mechanism design to enable programs such as demand response systems, revenue protection, etc. In our group, we have developed set of tools drawn from Generalized Principal Component Analysis, Sparse Subspace Clustering and other "Big Data Analytics" to begin to address these problems. A key requirement is to develop the algorithms to be hard real time algorithms and to assess their performance on experimental data where the ground truth is available or can be collected through experiments. Models of attack and defense of the algorithms need to be developed as well.

Project 4 Title - Robotic Manipulation with a Human in the Loop (advisor Prof. Ruzena Bajcsy)
Description - Recent years have seen significant research interest in semi-autonomous robotic systems for industrial, service, and a multitude of other applications. Semi-autonomous robots are broadly defined as robots that can solicit a human operator's input when they encounter a situation they are unsure how to deal with. This ability to consult a human when necessary allows semi-autonomous robots to perform more sophisticated tasks in more variable environments than their fully-autonomous cousins.

A number of questions must be answered in the design of a real world semi-autonomous robotic system: What is the task to be performed? What parts of the task will be performed autonomously? How will the robot decide when to stop and solicit human input? What will the operator interface look like?
For this project, you will design and implement a semi-autonomous robotic system to perform a pick and place manipulation task that might be encountered by a service or industrial robot. Such a task will include several phases, including identifying the object using vision or other sensors, finding stable grasp points on the object, and planning a collision-free trajectory to move the object from its initial to its final location. Depending on the specific application you choose, the system could solicit human input on which object to manipulate, where to place grasps to hold the object securely, where to move the object to, or other questions. The specific scenario you design the system for would be up to you, and could be a manufacturing, home, or other application depending on the specific interests of your team.

Potential Subprojects

Estimation of object pose and geometry using vision, depth, and other sensors

Signal Processing and Communications

Program Requirements

All EECS MEng students should expect to complete four (4) technical courses within the
EECS department at the graduate level, the Fung Institute's engineering leadership curriculum,
as well as a capstone project that will be hosted by the EECS department.

2014-2015 Capstone Projects

For the capstone projects for Master of Engineering in Electrical
Engineering and Computer Science (EECS) our department believes that
the students are going to have a significantly better experience if
the projects are followed closely by an EECS professor throughout the
academic year. To ensure this, we have asked the faculty in each area
for which the Master of Engineering is offered in our department to
formulate one or more project ideas that the incoming students will
have to choose from. We list below the titles and faculty advisor for
these capstone choices in the area. Depending on the number of
enrolled students in the area, we may run only a subset of these
project ideas.

Project 1 Title - Computational CellScope and Computation Illumination for Upgrading an Optical Microscope (advisor Prof. Laura Waller) - this project is cross-listed with
the Physical Electronics & Integrated Circuits area.
Description - We are building an inexpensive optical microscope based on mobile
phone technology (CellScope). By implementing illumination patterning in Fourier space, we
can create a computational imaging system that can image 3D and phase information. The
new computational CellScope will be used for diagnosing tropical diseases in underdeveloped
countries.

We are developing new methods for optical microscopy that use
sophisticated image processing and Fourier optics to achieve multiple contrast modes
in a commercial microscope with minimal hardware modification. We will provide
super-resolution capabilities with phase imaging, so that the microscope can
achieve gigapixel images with diffraction-limited resolution.

Project 2 Title - Scalable video-on-demand with edge resources (advisor Prof. Kannan Ramchandran)
Description - In our research group at Berkeley, we have recently developed an exciting new platform (theory and algorithms) for delivering Video-on-Demand (VoD) content in a highly scalable, robust, and distributed way with the aid of peer cooperation. Our approach is based on massively aggregating the "micro-resources" of storage, CPU, bandwidth, and connectivity available at peer edge devices like laptops and tablets. We have come up with the theory and a fully distributed algorithm that figures out how each edge device should interact with the rest of the system in such a way that everyone's resources are maximally utilized.

As a concrete application of this framework, imagine being able to deliver ultra-high-def (UHD) video quality having 16x the resolution of HD video, without any investment in additional infrastructure by seamlessly leveraging the available "spare" resources at the edges. Imagine a platform that can deliver UHD video at the same cost that you pay for Netflix today: isn't that cool? While we have developed the theory and algorithm, and observed its huge potential, much work remains to make it viable and practical. We would like to push this project forward into a real deployable system and change the way that video is delivered and watched in the near future.

Visual Computing and Computer Graphics

Program Requirements

All EECS MEng students should expect to complete four (4) technical courses within the
EECS department at the graduate level, the Fung Institute's engineering leadership curriculum,
as well as a capstone project that will be hosted by the EECS department.

2014-2015 Capstone Projects

For the capstone projects for Master of Engineering in Electrical
Engineering and Computer Science (EECS) our department believes that
the students are going to have a significantly better experience if
the projects are followed closely by an EECS professor throughout the
academic year. To ensure this, we have asked the faculty in each area
for which the Master of Engineering is offered in our department to
formulate one or more project ideas that the incoming students will
have to choose from. We list below the titles and faculty advisor for
these capstone choices in the area. Depending on the number of
enrolled students in the area, we may run only a subset of these
project ideas.

Project 1 Title - Interactive Device Design with Kinoma Create (advisors Prof. Bjoern Hartmann and Andy Carle, Marvell)
Description - Tight integration of innovative hardware and well-designed software, a combination that is greater than the sum of its parts, is the defining feature of today's best products. Seamless integrations do not happen incidentally. They are the result of thoughtfully co-designing hardware and software over the course of many successive iterations of prototypes. The result of this process can be amazing: user experiences custom tailored to exactly where, when, why, and how the product will be used. What, then, is the main challenge in achieving this result? Moving fast without wasting effort - quickly creating prototypes that not only answer questions, but also constantly lead you one step closer to a real product. Development tools either help or hinder this process. Finding the right tools - both for hardware and software - can make or break a project.

The Kinoma team at Marvell Semiconductor has developed one set of tools to address this challenge: Kinoma Create, a product prototyping toolkit; the Kinoma Platform Runtime, a JavaScript application framework for mobile and embedded devices; and Kinoma Studio, an Eclipse-based IDE for building Kinoma applications and simulating devices. We would like to work with you, the intrepid MEng student, to build a great product using them. In this project, you will work with the Kinoma team to brainstorm a brilliant product concept (consumer electronics, internet of things devices, office or classroom technology), build a prototype, test your prototype with real users, and iterate repeatedly over your design. We want to help you build an amazing device and will mentor you every step of the way. This project is an excellent fit for computer scientists (especially JavaScript developers), user experience/interaction designers, mechanical engineers, and new product developers.

Project 2 Title - Forensic Methods for Detecting Image Manipulation (advisor Prof. James O'Brien)
Description - Sophisticated photo editing software has made it increasingly easy to
manipulate digital images. Often visual inspection cannot definitively distinguish the
resulting forgeries from authentic photographs. When manipulated images are passed off
as authentic they facilitate hoaxes, fraud, and misinformation. Techniques in image
forensics aim to detect the geometric or statistical inconsistencies that result from
specific forms of photo manipulation, and definitively distinguish forgeries from
authentic photographs.

There are two options for this project:

The first is to develop new forensic methods based on geometric content analysis.
These methods focus on finding inconsistencies in the geometric relationships among
objects depicted in a photograph. The geometric relationships in the 2D image
correspond to the projection of the relations that exist in the 3D scene. If a
scene is known to contain a given relationship but the projected relation does
not hold in the photograph, then one may conclude that the photograph is not a
true projective image of the scene. The goal of this project is to build a set
of testable constraints that must be satisfied in real images. Where a constraint
is not satisfied there is definitive, objective evidence of image manipulation.

The second is to develop automated methods that can comb through large collections
of images and flag those which contain suspect irregularities that indicate
potential manipulation. Current automated methods do not offer definitive
proof of forgery, but they can be used as filter and search tools to select
images for subsequent definitive testing by geometric content analysis.

Project 3 Title - Affordable Internet Communication for Rural Areas (TIER) (advisor Prof. Eric Brewer)
Description - Building off of the technology of the Village Base Station project at TIER, this project serves to explore how we can make popular modes of Internet communication accessible in remote rural areas. Internet based communication channels such as WhatsApp and Facebook have become popular alternatives to traditional SMS in their cost effectiveness to the end-user. However, these mediums have not been optimized for the Lo-Fi, bandwidth constrained devices that are prevalent in rural areas. Students working on this project will face the challenge of adapting such media to simple interfaces that maximize usability. They will also analyze the feedback of users on the ground in rural areas, and collect data to explore the implications of these new communication channels on existing platforms. Experience with HCI, Networking and Security is preferred.

Capstone Projects

A unique and important feature of the Berkeley Masters of Engineering is the
capstone project experience. You will join a team of 3-5 students and pursue a
specific problem or opportunity that can be addressed by technology, and gain
direct experience in applying the skills you learn in your leadership courses.

Past and current EECS capstone projects

Integrated Circuits

Compressed sensing (Marvell and Professor David Allstot)

Report guidelines

The Fung Institute and your capstone course staff will guide you through the
leadership requirements and general guidelines for the project, while your
capstone faculty advisor will guide you through the technical aspects of the project.

A few reminders in terms of general guidelines:

You must have two faculty readers for your final report. One of those
faculty members must be from EECS.

All EECS students from one capstone project should have the same two faculty readers, even if
the students are in different areas of concentration.

Filing guidelines

Produce an M.Eng. Plan II Title/Signature Page. The Fung Institute will
provide the template for you.

Common Forms

There are numerous forms that you will need to fill out during your two semesters at UC Berkeley. The forms below are ONLY for the EECS department. Other offices on campus will notify you of important forms that you need to complete with them.

Degree Planning Form – Choose your technical courses from this Technical Courses page and
download the form,
meet with your faculty advisor before classes begin, have him sign the form, and then turn in the form to Breanne Tcheng, your Masters Student Services Advisor, in 205 Cory Hall by the end of the second week of classes.

Advancement to Candidacy – To inform the University that you are prepared to graduate, you must complete the courses listed on your Degree Planning Form and Breanne Tcheng will submit the Advancement to Candidacy form for you. If you decide to take different courses from your original Degree Planning Form, then please submit another one to Breanne by the end of your second week of classes in Spring.

Add/Drop Courses – If you need to add or drop a course (or change the number of units or grading option) after the second week of classes each semester, you must complete this Add/Drop form, get any necessary instructor signatures, have your faculty adviser sign, and submit it to Breanne Tcheng in 205 Cory. She can immediately fulfill the request and your CARS account will be billed accordingly.

Student Services Advisor

Your student services advisor is also available to you throughout your degree program to help you with all aspects of your experience at UC Berkeley.

You all have one advisor, Breanne Tcheng. Her office is located in 205 Cory Hall and you can stop by anytime M-F 9am-noon, 1pm-4pm. She will also hold specific office hours for M.Eng. students at 2150 Shattuck Street upon request. You can also email (btcheng@eecs) or call her (510-643-8107).

It is a good idea to go to her with all of your questions and she will be able to either answer the question herself or she can let you know where to go to get the answer or assistance you need. Please make sure that she always has your most updated contact information as she will be emailing you very important information and announcements.

International Students

Many of our admitted students in the MEng program are international students. For information about visas, please contact the International Office. Be sure to update your email address with the International Office as well as the EECS department.

EECS

Breanne TchengMasters Student Services Advisor
205 Cory Hall
Email for Admissions: GradAdmissions@eecs.berkeley.eduEmail for Current Students: btcheng@eecs.berkeley.edu(emails sent to btcheng@eecs regarding admissions will be forwarded to Gradadmissions@eecs and will be sent to the end of the queue. Please email Gradadmissions@eecs directly for fastest service.)